1. Field of the Invention
The present invention relates to improved ranking of search results.
2. Background Art
A search engine is an information retrieval system used to locate documents and other information stored on a computer system. Search engines are useful at reducing an amount of time required to find information. One well known type of search engine is a Web search engine which searches for documents, such as web pages, on the “World Wide Web.” The World Wide Web is formed by all publicly accessible websites, which primarily includes websites hosted on computer systems that are accessible over the Internet. Other types of search engines include personal search engines, mobile search engines, and enterprise search engines that search on intranets.
Development of a search engine that can index a large and diverse collection of documents, yet return to a user a short, relevant list of result documents in response to a query has long been recognized to be a difficult problem. A user of a search engine typically supplies a short query to the search engine, the query containing only a few terms, such as “hazardous waste” or “country music.” The search engine attempts to return a list of relevant documents. Although the search engine may return a list of tens or hundreds of documents, most users are likely to only view the top few documents on the list. Thus, to be useful to a user, a search engine is desired to be able to determine, from potentially billions of documents, the two or three documents that a user would be most interested in, according to the query submitted by the user.
Previously, search engine designers have attempted to construct relevance functions that take a query and a document as their input and return a relevance value. Relevance values may be used, for example, to create a list of documents indexed by the search engine. The list ranks the documents in order of relevance to the query. For the top two or three documents on this list to be useful to a user, the underlying relevance function must be able to accurately and quickly determine the relevance of a given document to a query.
A user's perception of true relevance of a document to a query is influenced by a number of factors, many of which are highly subjective. A user's preferences are generally difficult to capture in an algorithmic set of rules defining a relevance function. Furthermore, these subjective factors may change over time, such as when current events are associated with a particular query term. Changes over time in the aggregate content of the documents available in the Internet may also alter a user's perception of the relative relevance of a given document to a particular query. A user who receives a return list from a search engine that contains documents that the user does not perceive to be highly relevant may become frustrated, and may potentially abandon the use of that particular search engine.
Thus, what is needed are techniques for determining a document relevance function that reflects one or more human users' perceptions of document relevance to a query, and can rank documents quickly and efficiently.